Abstract: As described herein, a collaborative filtering system, method, and computer program provide a model used to calculate ranked predictions for subscribers. In use, data is received which correlates subscribers of a service provider with offers provided to the subscribers by the service provider, wherein each correlation is associated in the data with an indication of whether the offer was accepted by the subscriber. From the data, a plurality of unique correlations between subscribers and offers are determined. An implicit ranking is calculated for each unique correlation, based on the associated indication of acceptance for correlations matching the unique correlation. Input data is generated that includes each unique correlation with the implicit ranking calculated for the unique correlation. The input data is processed utilizing a collaborative filtering algorithm to generate a model configured to provide predicted implicit rankings for new correlations between subscribers and offers.

Abstract: A system, method, and computer program product are provided for generating intelligent automated adaptive decisions. In operation, a system receives a request to generate a prediction associated with a business problem for a customer. The system identifies a customer segment from a plurality of customer segments to which the new customer is most closely associated. Additionally, the system identifies a statistical model associated with the customer segment. Moreover, the system selects a best prediction from a competing set of machine learning models and the statistical model, utilizing a multi arm bandit arbitrator applying a multi arm bandit technique to solve the business problem.

Abstract: A system, method, and computer program product are provided for maintaining consistency between a NoSQL database and non-transactional content associated with one or more files. In operation, the system identifies one or more files including non-transactional data for maintaining consistency between the non-transactional data and a NoSQL database associated with the system. The system stores the non-transactional data associated with the one or more files in a transaction file. The system stores artifacts associated with the non-transactional data in a file with an ending marker and stores the non-transactional data with a corresponding transaction ID. The system stores data of the transaction file in the NoSQL database associated with the system. The system stores the transactional data with the corresponding transaction ID. The system scans the transaction file utilizing an asynchronous process to locate successful transactions.